Overview
This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.
The Deep Learning AMI based on Amazon Linux 2 is an optimized environment for building, training, and deploying deep learning models in the AWS Cloud. This AMI provides a powerful set of tools and libraries, including popular frameworks such as TensorFlow, PyTorch, Apache MXNet, and more, pre-installed and ready to use.
Key Features
- Pre-configured Frameworks: Easily access the latest versions of deep learning frameworks, facilitating rapid development and experimentation.
- GPU Support: Leverage GPU instances for accelerated compute performance, enhancing model training and inference times.
- Extensive Documentation: Includes comprehensive documentation and examples, allowing users to quickly onboard and start building.
- Development Tools: Integrated support for Jupyter Notebooks, making it convenient for interactive development and data visualization.
- Amazon S3 Integration: Simplified access to Amazon S3 for large datasets, ensuring efficient data handling and storage solutions.
Benefits
- Reduced Setup Time: Get started immediately with a ready-to-use environment, minimizing the overhead involved in software installation and configuration.
- Cost Efficiency: Pay only for what you use with flexible pricing options for EC2 instances, ensuring optimal resource utilization.
- Scalability: Easily scale your applications with AWS's infrastructure, allowing you to handle increasing workloads without interruption.
Use Cases
- Research and Development: Ideal for researchers and data scientists looking to develop and test deep learning models without the hassle of environment setup.
- Production Deployment: Deploy production-ready machine learning models efficiently, utilizing the robust AWS infrastructure to handle real-time inference.
- Education: Serve as a learning platform for students and professionals looking to gain hands-on experience with deep learning technologies and best practices.
Unlock the potential of deep learning in the cloud with the Deep Learning AMI on Amazon Linux 2, designed to enhance productivity and innovation for developers and data scientists alike.
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Highlights
- The Deep Learning AMI based on Amazon Linux 2 provides a comprehensive environment optimized for building and training machine learning models. Featuring popular frameworks such as TensorFlow, PyTorch, and Apache MXNet, it simplifies the setup process, allowing data scientists and engineers to focus on model development rather than infrastructure. With pre-installed packages, users can quickly run experiments or develop applications that leverage advanced AI capabilities.
- This AMI is particularly beneficial for organizations that require scalable and efficient resources for deep learning tasks. By integrating seamlessly with Amazon EC2, users can take advantage of the elasticity of the cloud to provision instances as needed, optimizing costs. With support for GPU acceleration, users can significantly reduce training times for complex models, making it ideal for both research and production environments.
- Moreover, the Deep Learning AMI supports a variety of use cases, from developing computer vision applications to natural language processing. Its robust feature set allows for easy deployment of AI solutions, whether for real-time inference or batch processing. Additionally, the AMI includes monitoring tools, enabling users to track performance metrics and make informed decisions to enhance their machine learning workflows.
Details
Typical total price
$2.30/hour
Features and programs
Financing for AWS Marketplace purchases
Pricing
- ...
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t1.micro | $0.07 | $0.02 | $0.09 |
t2.nano | $0.07 | $0.006 | $0.076 |
t2.micro AWS Free Tier | $0.21 | $0.012 | $0.222 |
t2.small | $0.07 | $0.023 | $0.093 |
t2.medium | $0.14 | $0.046 | $0.186 |
t2.large | $0.14 | $0.093 | $0.233 |
t2.xlarge | $0.28 | $0.186 | $0.466 |
t2.2xlarge | $0.56 | $0.371 | $0.931 |
t3.nano | $0.07 | $0.005 | $0.075 |
t3.micro AWS Free Tier | $0.07 | $0.01 | $0.08 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
The instance can be terminated at anytime to stop incurring charges
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
System Updates
Additional details
Usage instructions
SSH to the instance and login as 'ec2-user' using the key specified at launch.
OS commands via SSH: SSH as user 'ec2-user' to the running instance and use sudo to run commands requiring root access.
More on using Deep Learning AMI with Conda: https://docs.thinkwithwp.com/dlami/latest/devguide/tutorial-conda.html
Resources
Vendor resources
Support
Vendor support
Email support for this AMI is available through the following: https://supportedimages.com/support/ OR support@supportedimages.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
no NVIDIA gpu available
it has CUDA 10.0 but no NVIDIA gpu nor drivers installed. instead of it, there is
$ lspci | grep VGA
00:01.3 Non-VGA unclassified device: Intel Corporation 82371AB/EB/MB PIIX4 ACPI (rev 08)
00:03.0 VGA compatible controller: Amazon.com, Inc. Device 1111
Wasted my time trying to run a CUDA app